The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Parameter Setting in Evolutionary Algorithms
Open accessAbstract
One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.
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Cites
Genetic algorithms in search, optimization, and machine learning
(1989) · Choice Reviews Online · doi:10.5860/choice.27-0936 · Cited by 49,010
Genetic Programming: On the Programming of Computers by Means of Natural Selection
Koza, J. R. (1992) · Medical Entomology and Zoology · Cited by 13,082
Handbook of Genetic Algorithms
Davis, L. D. (1991) · Cumulative Index of Computer Aided Architectural Design · Cited by 7,330
Bäck, T. (1996) · Oxford University Press eBooks · doi:10.1093/oso/9780195099713.001.0001 · Cited by 5,113
Genetic Algorithms + Data Structures = Evolution Programs
Michalewicz, Z. (1996) · Springer eBooks · doi:10.1007/978-3-662-03315-9 · Cited by 5,095
Completely Derandomized Self-Adaptation in Evolution Strategies
Hansen, N., & Ostermeier, A. (2001) · Evolutionary Computation · doi:10.1162/106365601750190398 · Cited by 4,397
Handbook of Evolutionary Computation
(1997) · Institute of Physics eBooks · doi:10.1887/0750308958 · Cited by 2,990
Hansen, N., Müller, S. D., & Koumoutsakos, P. (2003) · Evolutionary Computation · doi:10.1162/106365603321828970 · Cited by 2,601
Parameter control in evolutionary algorithms
Eiben, A. E., Hinterding, R., & Michalewicz, Z. (1999) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.771166 · Cited by 1,980
*13 Simulated Annealing and Boltzmann Machines
(1993) · Neural Network Learning and Expert Systems · doi:10.7551/mitpress/4931.003.0017 · Cited by 1,637
Cited by
Exploration and exploitation in evolutionary algorithms: A survey
Črepinšek, M., Liu, S.-H., & Mernik, M. (2013) · ACM Computing Surveys · doi:10.1145/2480741.2480752 · Cited by 1,298
Parameter tuning for configuring and analyzing evolutionary algorithms
Eiben, A. E., & Smit, S. K. (2011) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2011.02.001 · Cited by 622
Fraser, G., & Arcuri, A. (2013) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2012.14 · Cited by 586
Parameter Control in Evolutionary Algorithms: Trends and Challenges
Karafotias, G., Hoogendoorn, M., & Eiben, A. E. (2015) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2014.2308294 · Cited by 516
Differential Evolution: A survey of theoretical analyses
Opara, K. R., & Arabas, J. (2019) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2018.06.010 · Cited by 473
Metadata
- Venue
- Studies in Computational Intelligence
- Publisher
- Springer Berlin Heidelberg
- Published
- 2007
- ISSN
- 1860-949X (ISSN-L)
- 1860-9503
- OpenAlex
- W1543258308
- Cited by
- 422
- References
- 31
- FWCI
- 7.79
- Type
- book
- Language
- en
- Open access
- green
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